# HG changeset patch
# User SylvainPL <sylvain.pannetier.lebeuf@umontreal.ca>
# Date 1268594224 14400
# Node ID c452e3a0a3b11bdff73b5109a3dd9a8674c0320c
# Parent  02ed13244133ebf3fa41898613984d16eaabe88a
Changement de la base de donnees qui sera utilisee

diff -r 02ed13244133 -r c452e3a0a3b1 deep/stacked_dae/v_sylvain/nist_sda.py
--- a/deep/stacked_dae/v_sylvain/nist_sda.py	Sun Mar 14 15:07:17 2010 -0400
+++ b/deep/stacked_dae/v_sylvain/nist_sda.py	Sun Mar 14 15:17:04 2010 -0400
@@ -37,8 +37,8 @@
 TEST_CONFIG = False
 
 #NIST_ALL_LOCATION = '/data/lisa/data/nist/by_class/all'
-JOBDB = 'postgres://ift6266h10@gershwin/ift6266h10_sandbox_db/fsavard_sda_v2'
-EXPERIMENT_PATH = "ift6266.deep.stacked_dae.v2.nist_sda.jobman_entrypoint"
+JOBDB = 'postgres://ift6266h10@gershwin/ift6266h10_sandbox_db/sylvainpl_sda_vsylvain'
+EXPERIMENT_PATH = "ift6266.deep.stacked_dae.v_sylvain.nist_sda.jobman_entrypoint"
 
 REDUCE_TRAIN_TO = None
 MAX_FINETUNING_EPOCHS = 1000
@@ -54,24 +54,24 @@
 # combined with produit_cartesien_jobs so we get a list of all
 # possible combinations, each one resulting in a job inserted
 # in the jobman DB.
-JOB_VALS = {'pretraining_lr': [0.1, 0.01],#, 0.001],#, 0.0001],
-        'pretraining_epochs_per_layer': [10,20],
-        'hidden_layers_sizes': [300,800],
-        'corruption_levels': [0.1,0.2,0.3],
+JOB_VALS = {'pretraining_lr': [0.1],#, 0.01],#, 0.001],#, 0.0001],
+        'pretraining_epochs_per_layer': [10],
+        'hidden_layers_sizes': [500],
+        'corruption_levels': [0.1],
         'minibatch_size': [20],
         'max_finetuning_epochs':[MAX_FINETUNING_EPOCHS],
-        'finetuning_lr':[0.1, 0.01], #0.001 was very bad, so we leave it out
-        'num_hidden_layers':[2,3]}
+        'finetuning_lr':[0.1], #0.001 was very bad, so we leave it out
+        'num_hidden_layers':[1,1]}
 
 # Just useful for tests... minimal number of epochs
 DEFAULT_HP_NIST = DD({'finetuning_lr':0.1,
                        'pretraining_lr':0.1,
                        'pretraining_epochs_per_layer':2,
                        'max_finetuning_epochs':2,
-                       'hidden_layers_sizes':800,
+                       'hidden_layers_sizes':500,
                        'corruption_levels':0.2,
                        'minibatch_size':20,
-                       'reduce_train_to':10000,
+                       #'reduce_train_to':10000,
                        'num_hidden_layers':1})
 
 '''